我遇到的问题是:在navicat mysql中从一台mysql服务器(正式)上传输数据到另外一台服务器(模拟数据库)。是整库传输。将模拟数
我遇到的问题是:在navicat mysql中从一台mysql服务器(正式)上传输数据到另外一台服务器(模拟数据库)。是整库传输。将模拟数据库中某一个库的数据文件夹重命名之后,重新创建一个新的数据库,再进行数据传输。传输完成之后,发现模拟上新建的数据库的表变为了只读。 通过按照下面文章的类似步骤,解决了问题。
这两天在进行网站搬家,这次网站搬家采用直接打包mysql数据库和网页文件的形式进行迁移,上传好mysql data目录里面的网站数据库至VPS上mysql存放数据库的目录里面,解压就行。我的VPS存放数据库的路径是 /usr/local/mysql/var。
上传好网站数据,解压,配置好数据库链接参数就行,网站就能正常连接上了,我本以为这已 经是顺利迁移完成了,但后来操作的时候,发现只能读取数据库的内容,不能更改写入任何信息,提示#1036 – Table ‘* ‘ is read only (*号为任意表),也就是说表只有只读属性。
通过SSH,给数据库文件777权限,admin是我的数据库文件夹
第一步: chmod -R 0777 /usr/local/mysql/var/admin/
给数据库目录的所属用户和组改为MySQL
1 第二步: chown -R mysql:mysql admin
但是这样还不能更改数据库,首先,找到mysqladmin所在位置,一般都在mysql/bin下面,,我的在/usr/local/mysql/bin 里面,还需要运行以下命令:
1 第三步: ./mysqladmin -u root -p flush-tables
之后输入root账号的密码,马上就好了,没有任何任何提示,然后测试一下,能正常读写,搬家也就顺利完成。
本文永久更新链接地址:

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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